Autonomous vehicles are developed to navigate and operate either unmanned or to assist a vehicle operator, and can utilize many different types of sensors, automation, robotics, and other computer-controlled systems and mechanisms. Inherently, autonomous vehicles are also developed with many active safety systems, which can not only increase driver comfort and reduce fatigue, but also reduce and/or eliminate vehicle injuries and deaths resulting from motor vehicle accidents. However, the many automated systems, sensors, and algorithms developed for use in an autonomous vehicle are costly and require considerable expertise to implement. Further, automobile companies and other vehicle manufacturers must each develop their own team of core competencies, technology infrastructure, and proprietary systems, which can be difficult and is cost prohibitive to include in mainstream consumer vehicles. To remain competitive in the marketplace, the companies and manufacturers that are unable to develop the internal competencies will need to partner with third parties that provide the autonomous vehicles systems. Likely, this will significantly decrease time to market for new vehicles and will tie a company to a third party proprietary system, which may be undesirable.
FIG. 1 illustrates an example of a conventional autonomous vehicle system 100, to include features of active safety systems. Generally, the autonomous vehicle system is representative of systems that include a centralized logging and data processing computer that receives sensor data input from a multitude of different sensors and components. Typically, these centralized systems have limited feature sets, as well as a lack of platform, sensor, and interface compatibility. Further, these centralized systems are susceptible to failure and can unexpectedly shut-down, such as due to cascading errors that cause the system to lockup, resulting in operation failure and potential loss of the autonomy platform. For example, an obstruction in the pathway of a vehicle may cause an unexpected failure of the simultaneous localization and mapping (SLAM) algorithm at 102, causing the fusion calculations of the ego motion to no longer converge at 104. Data flow through the ego motion (e.g., data received and communicated) can become blocked or stalled, resulting in a failure of the path planner at 106, and rendering the autonomous vehicle system inoperable and/or the vehicle immobile.